Dynamic Bayesian optimization method for batch distillation operation process

doi:10.11949/0438-1157.20241088

Abstract

Abstract:

Batch distillation is an important chemical separation technology that has significant advantages in processing small batches and multi-component production. To enhance the performance of batch distillation, researchers have proposed various batch distillation intensification structures, such as middle vessel batch distillation column (MVBDC) and dividing wall batch distillation column (DWBDC). This paper establishes dynamic simulation models for three typical structures: conventional batch distillation column (BDC), MVBDC, and DWBDC. It also establishes control systems and strictly optimizes the operational variables of the three batch distillation processes using Bayesian optimization algorithms. The results of strict optimization are compared in order to evaluate the advantages and disadvantages of these three structures. The findings indicate that the DWBDC has the shortest operating time and the best economic benefits, making it a superior batch distillation structure.

Key words: distillation, dynamic simulation, optimization, structure comparison, process intensification

摘要：

间歇精馏是一种重要的化工分离技术，在处理小批量、多组分生产中具有显著优势。为提高间歇精馏性能，研究者提出了多种间歇精馏过程强化结构，如中间储罐间歇精馏塔（MVBDC）、隔板间歇精馏塔（DWBDC）等。本文建立了传统间歇精馏塔（BDC）、MVBDC、DWBDC三种典型结构的动态仿真模型，搭建了控制系统，并通过贝叶斯优化算法对三种间歇精馏的操作变量进行了严格优化，通过分析严格优化后的结果对比了三种精馏过程结构的优劣。结果表明，DWBDC具有最短的操作时间和最好的经济效益，是一种优越的间歇精馏过程强化结构。

关键词: 精馏, 动态仿真, 优化, 结构对比, 过程强化

CLC Number:

TQ 028.8

Gonghan GUO, Huidian DING, Qiang LI, Shengkun JIA, Xing QIAN, Yang YUAN, Haisheng CHEN, Yiqing LUO. Dynamic Bayesian optimization method for batch distillation operation process[J]. CIESC Journal, 2025, 76(2): 755-768.

郭恭涵, 丁晖殿, 李强, 贾胜坤, 钱行, 苑杨, 陈海胜, 罗祎青. 间歇精馏操作过程的动态贝叶斯优化方法[J]. 化工学报, 2025, 76(2): 755-768.

Figures/Tables 17

Fig.1 Dynamic model of BDC

Fig.2 Structure and control system of MVBDC

Table 1 Parameters and functions of the concentration controllers in MVBDC

控制器	比例增益	积分时间/min	作用
CCtop	0.3	40	操纵回流量控制回流罐中杂质浓度
CClow	2.5	30	操纵再沸器热负荷控制 $S_{1}$ 中杂质浓度

Table 1 Parameters and functions of the concentration controllers in MVBDC

控制器	比例增益	积分时间/min	作用
CCtop	0.3	40	操纵回流量控制回流罐中杂质浓度
CClow	2.5	30	操纵再沸器热负荷控制 $S_{1}$ 中杂质浓度

Fig.3 Structure and control system of DWBDC

Table 2 Parameters and functions of the concentration controllers in DWBDC

控制器	比例增益	积分时间/min	作用
CCtop	0.1	30	操纵回流量控制回流罐中杂质浓度
CCmid	1.5	10	操纵液相分配比控制S₁中杂质浓度
CClow	42.0	22	操纵再沸器热负荷Q₂控制塔釜杂质浓度

Table 3 Feed， products and utility prices

项目	价格
BTX混合物原料	63.61 USD/kmol
苯	78.125 USD/kmol
甲苯	82.58 USD/kmol
邻二甲苯	93.36 USD/kmol
冷却水（25~30℃）	0.354 USD/GJ
低压蒸汽（5 bar，160℃）	13.28 USD/GJ
中压蒸汽（10 bar，184℃）	14.19 USD/GJ
高压蒸汽（41 bar，254℃）	17.7 USD/GJ

Fig.4 The flowsheet of Bayesian optimization

Table 4 Optimization variables and ranges

BDC		MVBDC		DWBDC
优化变量	变量范围	优化变量	变量范围	优化变量	变量范围
收集B阶段的回流比R₀	1.5~4.0	塔顶回流量初值F₀/(kg/h)	9500~13500	塔顶回流量初值F₀/(kg/h)	10000~16000
收集B阶段增大后的回流比R₁	6~8	$S_{2}$ 流股的阀门开度Vm/%	25~55	液相分配比初值β_l	0.45~0.90
BT切割阶段的回流比R₂	2~6	再沸器热负荷Q/(GJ/h)	2~7	Section1热负荷Q₁/(GJ/h)	3.8~5.0
切换到收集T阶段的临界浓度x_T	0.91~0.98			Section3热负荷初值Q₂/(GJ/h)	0~3.5
收集T阶段的回流比R₃	1~5
收集T阶段增大后的回流比R₄	6~9
TX切割阶段的回流比R₅	4~8
再沸器热负荷Q/(GJ/h)	4.0~7.5

Table 4 Optimization variables and ranges

BDC		MVBDC		DWBDC
优化变量	变量范围	优化变量	变量范围	优化变量	变量范围
收集B阶段的回流比R₀	1.5~4.0	塔顶回流量初值F₀/(kg/h)	9500~13500	塔顶回流量初值F₀/(kg/h)	10000~16000
收集B阶段增大后的回流比R₁	6~8	$S_{2}$ 流股的阀门开度Vm/%	25~55	液相分配比初值β_l	0.45~0.90
BT切割阶段的回流比R₂	2~6	再沸器热负荷Q/(GJ/h)	2~7	Section1热负荷Q₁/(GJ/h)	3.8~5.0
切换到收集T阶段的临界浓度x_T	0.91~0.98			Section3热负荷初值Q₂/(GJ/h)	0~3.5
收集T阶段的回流比R₃	1~5
收集T阶段增大后的回流比R₄	6~9
TX切割阶段的回流比R₅	4~8
再沸器热负荷Q/(GJ/h)	4.0~7.5

Table 5 The predicted values of the surrogate model at the newly added points

参数	第一次迭代	最后一次迭代
F₀/(kg/h)	13114.061	13195.633
β_l	0.613	0.569
Q₁/(GJ/h)	3.963	4.478
Q₂/(GJ/h)	1.111	1.830
利润函数预测值/(USD/h)	411.765	1108.945
利润函数实际值/(USD/h)	813.404	1068.874
样本点数量	40	120

Fig.5 Iteration curve

Table 6 Optimal operational variables

BDC		MVBDC		DWBDC
优化变量	最优值	优化变量	最优值	优化变量	最优值
R₀	3.047	F₀/(kg/h)	10563.967	F₀/(kg/h)	12209.509
x_T	0.924	Vm/%	37.418	β_l	0.628
R₁	6.983	Q/(GJ/h)	4.375	Q₁/(GJ/h)	4.559
R₂	5.904			Q₂/(GJ/h)	2.857
R₃	1.260
R₄	6.967
R₅	6.115
Q/(GJ/h)	7.228

Table 7 Optimal results of batch distillation

参数	BDC	MVBDC	DWBDC
B收集量/kmol	228.014	257.005	234.650
T收集量/kmol	200.483	227.173	228.736
X收集量/kmol	304.848	313.915	325.188
B纯度/%(摩尔分数)	99.00	99.03	99.08
T纯度/%(摩尔分数)	99.00	99.00	99.11
X纯度/%(摩尔分数)	99.00	99.20	99.00
总能耗/GJ	317.926	133.050	166.992
冷热工程总费用/USD	2190.663	9905.187	1202.905
产品收益/USD	62823.928	68145.549	67580.544
总时间/h	20.78	16.44	13.74
利润函数/(USD/h)	484.149	967.163	1101.085

Table 8 Feed rates of three types of batch distillation

项目	BDC	MVBDC	DWBDC
原料量/kmol	795.031	806.323	805.671
B摩尔分数/%	30.94	31.99	29.30
T摩尔分数/%	29.62	29.17	30.43
X摩尔分数/%	39.45	38.84	40.28

Fig.6 Top purity of BDC

Fig.7 Liquid holdup at the collection location of BDC

Fig.8 Product purity variation at the collection location of MVBDC and DWBDC

Fig.9 Product collection location liquid holdup variation curve of MVBDC and DWBDC

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